Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments.
Masakazu YoshimuraJunji OtsukaAtsushi IrieTakeshi OhashiPublished in: CoRR (2022)
Keyphrases
- wide variety
- recognition accuracy
- recognition rate
- automatic recognition
- object recognition
- noise level
- dynamic environments
- noisy environments
- feature extraction
- image noise
- pattern recognition
- noise model
- noisy data
- visual recognition
- neural network
- image recognition
- recognition algorithm
- input data
- shape recognition
- handwritten characters
- recognition scheme
- highly dynamic
- recognition process
- activity recognition
- action recognition
- high level